As the status of team members and relationships between them change over time, the importance of membership nodes in the academic team also change, so that the academic team organizational structure evolves. The chang...
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ISBN:
(纸本)9781538637906
As the status of team members and relationships between them change over time, the importance of membership nodes in the academic team also change, so that the academic team organizational structure evolves. The changes caused by the core members of the team led to the evolution of the team structure. Therefore, this paper presents a dynamic community discovery algorithm based on temporal coauthor network. By detecting the importance of nodes, the strength of relative edges, and its variation of persistence with time, the proposed algorithm implements creation, extension, shrink, division and disappearance operations on the communities in order to achieve the purpose of dynamic community discovery. In addition, for assessing the quality of community division, the paper proposes a method based on the interest similarity of Chinese key characters feature of academic teams. In experiment, a public document record dataset and several synthetic dataset are used to verify the effectiveness our algorithm.
Software defined networks always need to migrate flows to update the network configuration for a better system performance. However, the existing literature does not take flow path overlapping information into conside...
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ISBN:
(纸本)9781538637906
Software defined networks always need to migrate flows to update the network configuration for a better system performance. However, the existing literature does not take flow path overlapping information into consideration when flows' routes are re-allocated. Consequently, congestion happens, resulting in deadlocks among flows and link resources, which will block the update process and cause severe packet loss. This paper resolves deadlocks with the help of spare resources during the network update. An algorithm is proposed to determine the feasibility of the consistent flow migration. We demonstrate that even if there are multiple consistent migration plans, finding the optimal one that occupies the fewest leisure bandwidth resources is NP-hard. An approximation algorithm is proposed to sequentially migrate flows in a consistent way. Extensive simulations show that our solution achieves a much smaller traffic loss rate at the cost of an affordable spare link resource usage compared to prior methods.
Currently loud data centers exist problems of load imbalance and high power consumption. This paper studies the virtual machine placement policy in cloud environment by applying live migration techniques, and proposes...
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ISBN:
(纸本)9781538637906
Currently loud data centers exist problems of load imbalance and high power consumption. This paper studies the virtual machine placement policy in cloud environment by applying live migration techniques, and proposes a target host selection algorithm MOGA-THSA based on MOGA. As a heuristic algorithm, through designing excellent genetic operators and fitness functions, it optimizes the load balance and power consumption of the data center with smaller SLA violation rate. The algorithm is implemented on simulation platform CloudSim, and experiments show that it can improve the load balance of cloud data center and decrease total power consumption effectively, thus having a certain guiding significance for researching the virtual machine placement policy.
The Euler tour technique is a classical tool for designing parallel graph algorithms, originally proposed for the PRAM model. We ask whether it can be adapted to run efficiently on GPU. We focus on two established app...
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ISBN:
(纸本)9781665440660
The Euler tour technique is a classical tool for designing parallel graph algorithms, originally proposed for the PRAM model. We ask whether it can be adapted to run efficiently on GPU. We focus on two established applications of the technique: (1) the problem of finding lowest common ancestors (LCA) of pairs of nodes in trees, and (2) the problem of finding bridgis in undirected graphs. In our experiments, we compare theoretically optimal algorithms using the Euler tour technique against simpler heuristics supposed to perform particularly well on typical instances. We show that the Euler tour-based algorithms not only fulfill their theoretical promises and outperform practical heuristics on hard instances, but also perform on par with them on easy instances.
Mining job scheduling features based on extraction and analysis of workload trace in high performance computing clusters can be used to optimize scheduling strategy and enhance system performance. Based on detailed an...
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ISBN:
(纸本)9781538637906
Mining job scheduling features based on extraction and analysis of workload trace in high performance computing clusters can be used to optimize scheduling strategy and enhance system performance. Based on detailed analysis of workload trace from a gene sequencing high performance computing system, this paper proposes a multi-queue backfilling scheduling algorithm, which is based on traditional backfilling scheduling. While optimizing for memory resource demands, this algorithm provides queue level load balancing to deal with the innate load imbalance characteristics of high performance systems. Experimental results based on practical gene sequencing workload trace clearly demonstrate that compared with traditional scheduling algorithms, the algorithm proposed in this paper is a good strategy to reduce the job waiting time and improve resource utilization.
In order to guarantee the reliability of services and reduce the waste of resources in traditional dual-path protection method, a service-reliability-based resources mapping method is proposed in this paper. The virtu...
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ISBN:
(纸本)9781538637906
In order to guarantee the reliability of services and reduce the waste of resources in traditional dual-path protection method, a service-reliability-based resources mapping method is proposed in this paper. The virtualization technology is adopted in our method for smart grid Fiber-Wireless access networks. Firstly, a priority-and fault-probability based primary link mapping model is set up. It classifies the service priorities level and provides high-priority services with high-reliability links to improve service reliability of the whole network. Then, a resource-saving aimed backup link mapping model is established to allocate the multiple services as many as possible for one backup link to save resources. At last, the genetic algorithm is used to solve the mapping model. The evaluation results show that our proposed method increases service reliability, and improves resource utilization.
In this paper, we propose an accurate contactless pose estimation method for the pose of a target in the earth coordinate frame using a mobile phone equipped with a camera and an inertial measurement unit (IMU). Under...
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ISBN:
(纸本)9781538637906
In this paper, we propose an accurate contactless pose estimation method for the pose of a target in the earth coordinate frame using a mobile phone equipped with a camera and an inertial measurement unit (IMU). Under the Manhattan world assumption, we first estimate the relative pose between the target and the camera using an existing line-based pose estimation method and then seek the target's pose in the earth frame by combining the visual pose and the IMU orientation. To improve the overall estimation accuracy, we propose a new camera-IMU relative pose calibration method, where we take the different stochastic nature the accelerometer and magnetometer measurements into consideration, and propose a new a consistency measure defined on elevation and azimuth angles. When compared to state-of-the-art methods, it demonstrates strong advantage on both elevation and azimuth estimation accuracy while featuring convenient calibration setting-up. We also report the improved overall pose estimation accuracy based on evaluations on a real-world dataset using our method, in contrast to an uncalibrated phone.
In the last years, the performance and capabilities of Graphics processing Units (GPUs) improved drastically, mostly due to the demands of the entertainment market, with consumers and companies alike pushing for impro...
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ISBN:
(纸本)9781424437511
In the last years, the performance and capabilities of Graphics processing Units (GPUs) improved drastically, mostly due to the demands of the entertainment market, with consumers and companies alike pushing for improvements in the level of visual fidelity, which is only achieved with high performing GPU solutions. Beside the entertainment market, there is an ongoing global research effort for using such immense computing power for applications beyond graphics, such as the domain of general purpose computing. Efficiently combining these GPUs resources with existing CPU resources is also an important and open research task. This paper is a contribution to that effort, focusing on analysis of performance factors of combining both resource types, while introducing also a novel job scheduler that manages these two resources. Through experimental performance evaluation, this paper reports what are the most important factors and design considerations that must be taken into account while designing such job scheduler.
The stream processing paradigm is used in several scientific and enterprise applications in order to continuously compute results out of data items coming from data sources such as sensors. The full exploitation of th...
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ISBN:
(纸本)9781538655559
The stream processing paradigm is used in several scientific and enterprise applications in order to continuously compute results out of data items coming from data sources such as sensors. The full exploitation of the potential parallelism offered by current heterogeneous multi-cores equipped with one or more GPUs is still a challenge in the context of stream processingapplications. In this work, our main goal is to present the parallel programming challenges that the programmer has to face when exploiting CPUs and GPUs' parallelism at the same time using traditional programming models. We highlight the parallelization methodology in two use-cases (the Mandelbrot Streaming benchmark and the PARSEC's Dedup application) to demonstrate the issues and benefits of using heterogeneous parallel hardware. The experiments conducted demonstrate how a high-level parallel programming model targeting stream processing like the one offered by SPar can be used to reduce the programming effort still offering a good level of performance if compared with state-of-the-art programming models.
Since they were introduced, Java streams were very fast embraced by the industry, being currently used at a large scale. The parallelism enabled by them is very easy to achieve, but it is constrained either by the use...
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ISBN:
(纸本)9781728174457
Since they were introduced, Java streams were very fast embraced by the industry, being currently used at a large scale. The parallelism enabled by them is very easy to achieve, but it is constrained either by the used parallelism model (in some cases), or by the set of operations that could be specified using streams. We investigate in this paper the possibility to enhance the computation types that could be defined using the Java streams API by introducing into this infrastructure the PowerList theory based computation. Powerlists are recursive data structures that together with their associated algebraic theory offer both abstractions in order to ease the development of parallelapplications, and also a methodology to design parallel algorithms. The Java streaming infrastructure could be adapted to support them in a great measure. We present here such an adaptation, and we analyse and discuss the advantages and constraints. This analysis is exemplified by application examples.
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